How Thermal Diffusivity Affects the Build Temperature in the SLS Process

Conductive fillers in polymer powder, like copper spheres and flakes, influence Additive Manufacturing processes. Learn how laser flash analysis allows determination of process setting to print highest quality parts.

In a previous article, we explained the motivation to add conductive fillers to PA12 powders and create complex components for thermal management with the Selective Laser Sintering (SLS) process. We also explained the different steps of sample preparation, which is crucial for the quality of the results.

Different print temperatures for different powder mixtures

The samples were prepared as part of a study [1] by researchers at the Institute of Polymer Technology (LKT) at the University of Erlangen-Nuremberg. They used different mixtures of copper spheres and flakes in varying contents: 5 and 10 vol% copper spheres and 5 vol% copper flakes. The energy density of 0.043 J/mm2 was kept constant for all materials to detect any changes in the process behavior due to the fillers. For the PA12/Cu spheres powder, a build temperature of 167°C was experimentally determined. For the PA12/Cu flakes mixture, the build temperature needed to be increased to 173°C. It was assumed that a higher thermal conductivity and lower specific heat capacity could be the reason. Therefore, the following analysis can be used to investigate these effects in detail.

How to analyze thermal diffusivity

At NETZSCH Analyzing & Testing, an LFA 467 Hyperflash® was used to measure the thermal diffusivity of these different mixtures of PA12 powder with copper particles in comparison to the neat PA12 material. 

A short light pulse heats the bottom surface of the sample and the temperature rise on the rear surface is measured as a function of time using an IR detector.

This is repeated for each temperature step after the sample temperature is stabilized and the flash lamp is also fired several times over a span of minutes.

The preparation of the samples is very important and explained in detail here.

After loading the samples, the measurement is started using the conditions summarized in the following table:

Table 1: Measurement conditions  

Sample holderZ-direction: 12.7 mm square x- and y-direction: laminate sample holder 12.7 mm
Atmosphere N2 
Gas flow100 ml/min
Temperature measuring points25, 40, 60, 80, 100, 120, 140, 160, 168, 180°C

How copper spheres influence thermal diffusivity

The NETZSCH Proteus® software automatically fits a suitable model to the measured data to allow the calculation of the half-times, Figure 1.

Figure 1: Example of detector signal as a function of time at 25°C with the fitted curve (red) for the sample with 5 vol% Cu spheres

Figure 2 shows the analyzed thermal diffusivity as a function of temperature and sample orientation for the neat PA12 in comparison to the PA12/copper sphere mixtures.

Figure 2: Temperature dependence of thermal diffusivity in three measurement directions: Comparison of the neat PA 12 sample and the PA 12/Cu spheres mixture

As expected, the neat PA12 samples show no directionality and the thermal diffusivity values are lowest. They show the typical decrease with increasing temperature up to the melting temperature.

The samples with 5 vol% Cu spheres show slightly higher values for the thermal diffusivity than the neat PA12 and the samples with 10 vol% Cu spheres show the highest values of the three materials. This is a result to the higher thermal diffusivity of the copper compared to the insulating matrix. For most samples, no directionality is observed due to the isotropic properties of the spheres. However, for the sample with 10 vol% Cu spheres in the thickness direction z, the thermal diffusivity is slightly lower than for the other two directions. This is likely related to the higher porosity of these samples, which was measured by Lanzl et al. [1]. The LFA results indicate higher porosity between layers in the z-direction than within a layer in the xy-plane.

How copper flakes influence the thermal diffusivity

A different behavior is observed with the copper flakes as shown in Figure 3, where the thermal diffusivity measurements of all samples in the x-direction and of the flakes in all three directions are compared.

Figure 3: Temperature dependence of thermal diffusivity in three measurement directions: Comparison of the PA 12/Cu flakes and isotropic materials (blue – only x-direction)

The flakes show much higher values for the thermal diffusivity than the other mixtures with spheres and the neat PA12. The high degree of anisotropy is expected based on the 2D character of the filler. The highest thermal diffusivity is measured in the y-direction followed by the x-direction. The lowest values are achieved through the thickness of a layer in the z-direction. This indicates a higher preferential orientation in the xy-plane, which is likely due to the powder application process.

Figure 4 shows a microscopy image of the cross-section of a single layer of the PA12/Cu flake mixture as reported by Lanzl et al. [1]. The image shows that the particles touch each other and therefore, the overall thermal resistance of the material (or here cross-section) should be minimized. The majority of the fillers is oriented horizontally, which corresponds to the xy-plane. However, it can be seen that some flakes are tilted at an angle, which results in the higher thermal diffusivity in the z-direction compared to all other samples. 

Thermal diffusivity measurements provide significant insight into both the orientation of the fillers and their vicinity to each other without the need for additional optical imaging.

Figure 4: Single layer of PA12 and 5 vol% copper flakes [1] 

How to determine the thermal conductivity

For further analysis or simulation, in addition to the thermal diffusivity, a, the thermal conductivity, l, is needed. To compute the thermal conductivity, the specific heat capacity, cp, and the density, r are required: 

λ(T)=a(T)∙cp(T)∙ρ(T)

Both the thermal diffusivity and specific heat capacity are measured as a function of temperature. The measurement and results of the cpmeasurements are explained here. However, the density requires reusing the density at room temperature as well as the thermal expansion coefficient for the investigated temperature range:

ρ(T)=ρRT∙αv(T)

The density at room temperature was measured by the buoyancy-flotation method with water, the thermal expansion coefficient, α, is measured with a Thermomechanical Analyzer (TMA), which will be explained in a later article. The coefficient of expansion is direction dependent und is calculated, it is calculated as follows

αv = (αx + αy + αz)/3

Higher copper content = Higher thermal conductivity

The resulting computed thermal conductivity values are plotted in Figure 6 as a function of temperature for the different materials and mixtures.


Figure 5: Temperature dependence of the Thermal conductivity in three directions for neat PA 12 and PA12/Cu mixtures

The same trends as seen for the thermal diffusivity are observed:

  • With increasing copper content, the thermal conductivity is increasing.
  • The Cu spheres show mainly isotropic behavior. Differences in the values are related to the porosity of the samples.
  • The copper flakes show the highest increase in thermal conductivity as the fillers partly touch and reduce the conductivity resistance of the composite material.
  • The copper flakes show anisotropic behavior due to their 2D geometry and the powder application process.

However, the reduced temperature dependence as well as the slight curvature at low temperatures is related to the temperature dependence of the cp values.

Optimizing process settings based on analysis results

For the application of such conductive fillers in thermal management, it is important to adjust the orientation of the 3D-printed parts to account for any anisotropy due to the coating process and filler geometry.

Regarding the process settings and in particular the build temperature, it was observed that the mixture of the flakes needed to be processed at a build temperature of 173°C, which was 6°C higher than the mixtures with spheres. The higher thermal conductivity and the lower specific heat both lead to a reduced ability of heat storage in the compound and better discharging of the heat. Especially in the xy-plane, where the highest conductivities with Cu flakes were obtained, it is to be expected that the energy input from the laser is more rapidly distributed, leading to a lower temperature. Thus, increasing the build temperature is counteracting this effect.

For better understanding the influence of the different filler shapes on the energy input, Lanzl et al. analyzed the thickness of a single layer. It was found that the layer thickness of the mixture with Cu flakes is significantly thinner. The researchers attributed this to the increased thermal conductivity in the xy-plane compared to the thickness direction and also to the increased diffuse reflection of the laser, which results in lower energy input. This additional analysis highlights the importance of understanding the changes in thermal diffusivity and conductivity for all aspects of the SLS process and the most suitable process settings.

About Institute of Polymer Technology (LKT)

The Institute of Polymer Technology is an academic research institute at the Friedrich-Alexander University of Erlangen-Nuremberg. It is one of the leaders in Additive Manufacturing research; particularly SLS. Other main research areas include Lightweight Design and FRP, Materials and Processing, Joining Technology and Tribology. In addition to these research focuses, the institute is also working on cross-disciplinary topics such as Filler Material ­Compounding, Simulation of Processing and Applications, Radiation Cross-linked Thermoplastics, Gentle Processing and many more.

Sources

[1] Lanzl, L., Wudy, K., Greiner, S., Drummer D., Selective Laser Sintering of Copper Filled Polyamide 12: Characterization of Powder Properties and Process Behavior, Polymer Composites, pp. 1801-1809, 2019: Selective laser sintering of copper filled polyamide 12: Characterization of powder properties and process behavior – Lanzl – 2019 – Polymer Composites – Wiley Online Library

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